Bibliographic record
Abstract
[In essays first published earlier this year in mainstream Australian media to considerable fanfare, Bagaric and Clarke, two Australian academics, develop a modest proposal for the justification of torture under excep- tional circumstances. This essay rebuts the proposal and defends the abso- lute prohibition against torture. Their attempt to abstract torture from the social context – including the “war on terror” – in which the question of government sanctioned torture is now being raised, is condemned as in- genuous. A rhetorical analysis further demonstrates that the authors them- selves do not believe their argument is either hypothetical or limited. Furthermore, when the actual “defence of torture” is examined, it is shown to be illogical, incoherent, and lacking any sophisticated under- standing of the nature, purpose, or effects of torture. This is not the first time that half-baked reasoning and careless analogies have been devel- oped in order to defend the indefensible. Drawing on Voltaire and Jona- than Swift as well as Guantanamo Bay, this essay puts an important social issue into its immediate and its larger historical context.]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.048 | 0.015 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".